Circulating tumor DNA profiling approach based on in silico background elimination guides patient classification of multiple cancers

Circulating tumor DNA (ctDNA) analysis is increasingly providing a promising minimally invasive alternative to tissue biopsies in precision oncology. However, current methods of ctDNA mutation profiling have limited resolution because of the high background noise and false-positive rate caused by benign variants in plasma cell-free DNA (cfDNA), majorly generated during clonal hematopoiesis. Although personalized parallel white blood cell (WBC) genome sequencing suppresses the noise of clonal hematopoiesis variances observed in ctDNA based liquid biopsy, the system cost and complexity restrict its extensive application in clinical settings. To address this challenge, we describe a Matched WBC Genome sequencing Independent CtDNA profiling (MaGIC) approach, which enables the sensitive detection of recurrent tumor mutant information harbored by ctDNA from a bulk cfDNA background based on hybrid capture cfDNA deep sequencing, in silico background elimination, and a reliable readout measurement by the calculation the number of key mutated exons. Leveraging somatic mutation data from 10163 patients across 24 cancer types obtained from The Cancer Genome Atlas, we confirm that the MaGIC approaches are of ideal performance in prediction of prognosis by tissue biopsy samples of patients across multiple cancers. Meanwhile, MaGIC approaches enable the classification of prostate cancer patients from heathy cohorts by ctDNA sequencing data. We further profiled the ctDNAs of 80 plasma samples from 40 patients with nasopharyngeal carcinoma before and during chemotherapy by MaGIC approaches. The MaGICv2 can predict the chemosensitivity with high accuracy by simply using one liquid biopsy sample of each patient before a stereotypical treatment course. We anticipate that this new approach has the potential utility of ctDNA detection in multiple clinical cancer contexts, thus facilitating precise cancer therapy. Teaser A liquid biopsy analysis method for multifunctional patient classification such as diagnosis and chemosensitivity prediction. ### Competing Interest Statement The authors have declared no competing interest.